Friday, September 9, 2016

In a couple of weeks I'm heading off to WEFTEC, the major annual North American conference for poop engineers like myself. This year I'll be participating in a breakfast meeting where we'll discuss my firm's offerings for smart analytics which sits under the umbrella of our Smart Integrated Infrastructure group.

M is for Measure

Firstly, and perhaps most importantly we need to focus on the measurements. What do we need to measure (and where)? How do we measure it? And what confidence do we have in that measurement? It might seem simple to say we need to be measuring the right parameters in the right place but in my experience this is the place where we've fallen down over the years, particularly when it comes to measurements in the extremely fouling environment of wastewater. All too often people have taken standard environmental monitors for water, streams or rivers or - worse still - lab instruments, and plonked them into poop water hoping they'll work. Unfortunately wastewater is not forgiving. In the late 1980's and early 1990's my old boss Dr John Watts did some great work in looking at the need for good calibration and validation in order to trust your data. Unfortunately he didn't publish much internationally, but here is one paper on the topic. More recently Oliver Grievson in his review of activated sludge instrumentation to celebrate 100 years of AS gave a nod to John's work in producing an online respirometer (and I'm still waiting for someone to produce something nearly as good - maybe the ASP-CON?)

A is for Analyze

The focus of a lot of the buzz right now is on "smart analytics" and the ability of software developed in the Internet age to handle "big data." That's all pretty cool. I always joke about wastewater having a problem with "crap data" rather than big data, but assuming we can figure out the "M" of measure, then there are now plenty of sophisticated tools to help us manage and analyze our data. All the big guys in IT are getting into this space, including the now famous Watson at IBM and now Microsoft with their PowerBI (I need to find time to play with that sometime as it looks pretty cool).

D is for Decide

OK, we have lovely measurements, producing pretty graphical representations of our big data... now what? This will be the fun part. Right now, most systems I've seen, leave the decide step to the operator or plant engineer. They have the expert knowledge which, coupled with insights from the advanced data analytics, are a powerful combination to help optimize a plant. The step beyond this is to add in automated control actions based on the input from the smart analytics. This is sort of like the jump to an autonomous vehicle which makes many people nervous but ultimately will give us the best performance overall.

About Me

A wastewater engineer since the early 90's, originally from the UK, now living in Kansas with a brief but wonderful interlude in Western Australia. Interested in sustainability, water issues, process modeling and online instrumentation. Also interested in social media and most things vaguely geeky.